Struct aws_sdk_rekognition::types::TestingData

#[non_exhaustive]
pub struct TestingData {
    pub assets: Option<Vec<Asset>>,
    pub auto_create: bool,
}

The dataset used for testing. Optionally, if AutoCreate is set, Amazon Rekognition uses the training dataset to create a test dataset with a temporary split of the training dataset.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

assets: Option<Vec<Asset>>

The assets used for testing.

auto_create: bool

If specified, Rekognition splits training dataset to create a test dataset for the training job.

Implementations

impl TestingData

pub fn assets(&self) -> &[Asset]

The assets used for testing.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .assets.is_none().

pub fn auto_create(&self) -> bool

If specified, Rekognition splits training dataset to create a test dataset for the training job.

impl TestingData

pub fn builder() -> TestingDataBuilder

Creates a new builder-style object to manufacture TestingData.

Trait Implementations

impl Clone for TestingData

fn clone(&self) -> TestingData

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for TestingData

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl PartialEq for TestingData

fn eq(&self, other: &TestingData) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for TestingData